Package | Description |
---|---|
messif.buckets |
Storage classes capable of holding
objects . |
messif.pivotselection |
Support for selection of representative objects (pivots).
|
messif.utility |
Various utilities that does not fit anywhere else including
a main class for executing batch files.
|
Modifier and Type | Method and Description |
---|---|
protected AbstractPivotChooser |
BucketDispatcher.createAutoPivotChooser(LocalBucket bucket)
Creates a new pivot chooser for the provided bucket.
|
AbstractPivotChooser |
BucketDispatcher.getAutoPivotChooser(int bucketID)
Returns pivot chooser that was automatically created for a bucket of this dispatcher.
|
Modifier and Type | Method and Description |
---|---|
java.lang.Class<? extends AbstractPivotChooser> |
BucketDispatcher.getAutoPivotChooserClass()
Returns the class of the pivot chooser that is currently used for buckets in this dispatcher.
|
Modifier and Type | Method and Description |
---|---|
void |
BucketDispatcher.setAutoPivotChooser(AbstractPivotChooser autoPivotChooserInstance)
Set the pivot chooser instance that chooses pivots for all the buckets in this dispatcher.
|
Modifier and Type | Method and Description |
---|---|
void |
BucketDispatcher.setAutoPivotChooser(java.lang.Class<? extends AbstractPivotChooser> autoPivotChooserClass)
Set the class of pivot chooser that will be created whenever a bucket is created by this dispatcher.
|
Modifier and Type | Class and Description |
---|---|
class |
ClusterPivotChooser
This pivot chooser selects a varying number of pivots based on cluster sizes which are limited by the parameter passed to the constructor.
|
class |
CoveragePivotChooser
This pivot chooser selects the pivots in a way that a good coverage of data by ball regions with centers in pivots and radius equal
to a fixed value (threshold) is ensured.
|
class |
FilteredRandomPivotChooser
FilteredRandomPivotChooser provides the capability of selecting a random object from the data set
passed to
FilteredRandomPivotChooser.selectPivot(int, messif.objects.util.AbstractObjectIterator) . |
class |
HierarchicalKMeansPivotChooser
Hierarchical k-means/medoids pivot chooser.
|
class |
IncrementalIDistanceChooser
Chooses pivots according to a generalized iDistance clustering strategy.
|
class |
IncrementalPivotChooser
Incremental selection of pivots.
|
class |
KMeansComputedPivotChooser
This class uses the k-means algorithm to cluster the objects,
so artitifial pivots are created as mean vectors from the cluster objects.
|
class |
KMeansPivotChooser
This class uses the k-means algorithm adapted for metric spaces to cluster the objects,
so it is k-medoids algorithm in fact.
|
class |
OnFlyRandomPivotChooser
OnFlyRandomPivotChooser provides the capability of selecting a random object from the whole bucket.
|
class |
OutlierPivotChooser
Selects pivots as outliers from the sample set.
|
class |
RandomPivotChooser
RandomPivotChooser provides the capability of selecting a random object from the whole bucket.
|
class |
SimpleClusterPivotChooser
This pivot chooser selects a varying number of pivots based on cluster sizes
which are limited by the parameter passed to the constructor.
|
class |
StreamSequencePivotChooser |
class |
TwoDistantIncrementalPivotChooser
This class provides a pivot chooser that selects maximally two pivots.
|
Modifier and Type | Method and Description |
---|---|
static VoronoiPartitioning.Result |
VoronoiPartitioning.doVoronoiPartitioning(AbstractPivotChooser chooser,
AbstractObjectList<LocalAbstractObject> dataObjects)
Partition the passed data into Voronoi cells.
|
static int |
VoronoiPartitioning.getClosestPivotIndex(AbstractPivotChooser chooser,
LocalAbstractObject dataObject)
Identify the closest pivot in the passed pivot chooser, so a corresponding Voronoi cell can be populated.
|
static long[] |
VoronoiPartitioning.getKClosestPivotsIndexes(AbstractPivotChooser chooser,
int k,
LocalAbstractObject dataObject)
Identify the "k" closest pivots in the passed pivot chooser, so corresponding Voronoi cells can be identified (and somehow processed).
|